The Challenge:
Legal leaders are balancing more change than ever—AI disruption, cost pressures, shifting expectations, and new definitions of value.
The Reality:
The most forward-thinking GCs are rewriting their playbooks, turning uncertainty into clarity, and risk into strategy.
What You’ll Learn:
--- How leading law departments are measuring impact and defining value beyond cost savings
--- What trends are shaping investment, hiring, and innovation priorities for 2026
--- The playbook top GCs use to stay adaptive and decisive amid constant change
Key Takeaway:
The future isn’t coming—it’s already here. The question is: how ready is your team to lead it?

The Challenge:
Legal teams are under pressure to adopt AI fast — but speed without readiness leads to wasted spend, low adoption, and tools that never solve the real pain points. The market is moving quickly, but not always in ways that match your roadmap or your reality.
The Reality:
Myah has spent the past year evaluating AI tools while simultaneously leading an enterprise-wide CLM rollout. Through disciplined testing, waiting, validating, and sequencing, she learned that the biggest strategic advantage isn’t early adoption — it’s intentional adoption. Her case study with Jurist reveals why timing, integration readiness, and accuracy matter more than market buzz or vendor momentum.
What You’ll Learn:
--- A proven framework for evaluating AI tools based on readiness, accuracy, integration, and adoption potential
--- How to differentiate hype-driven products from solutions that actually solve your problems
--- A real case study showing how waiting 12 months resulted in immediate ROI
Key Takeaway:
Progress isn’t about being first — it’s about being ready. The smartest AI teams win by choosing wisely, not quickly.

The Challenge:
Today’s General Counsel isn’t just managing risk—they’re managing reinvention.
The Reality:
The GC’s chair now sits at the strategy table, where decisions on AI, data, and ethics shape the enterprise.
What You’ll Learn:
--- How leading GCs are redefining influence and leading enterprise transformation
--- Frameworks for cross-functional collaboration with finance, IT, and business ops
--- Real examples of GCs driving measurable business outcomes through innovation
Key Takeaway:
Leadership in 2026 is about more than practicing law—it’s about building the business of law.

The Challenge:
AI isn’t just changing tools—it’s changing talent. The skills that got us here won’t get us there.
The Reality:
Legal departments are learning to “newskill,” not just “upskill”—building fluency in data, design, and decision intelligence.
What You’ll Learn:
--- How to identify and develop the skills that make teams future-ready
--- The structure of a modern AI literacy or data fluency program that works
--- How forward-leaning teams are fostering curiosity and experimentation
Key Takeaway:
The next great skill in legal isn’t coding—it’s curiosity.

The Challenge:
With every platform promising transformation, how do you know which AI tools are actually built for legal?
The Reality:
The real differentiator isn’t what these tools do—it’s how they think, learn, and integrate.
What You’ll Learn:
--- How to evaluate competing LLMs and choose the right ecosystem for legal use
--- What’s working inside real-world legal ops and eDiscovery implementations
--- How to future-proof your stack as enterprise AI evolves
Key Takeaway:
The smartest teams aren’t picking tools—they’re building ecosystems.

The Challenge:
Many legal teams are building agents for efficiency—but the real opportunity is driving growth.
The Reality:
Productivity agents streamline the present. Growth agents reshape the future—unlocking insight, revenue, and strategy-level value.
What You’ll Learn:
--- The difference between agents that automate and agents that innovate
--- Real-world examples of “growth agents” driving business outcomes
--- Frameworks for measuring success beyond time savings
Key Takeaway:
Don’t just save time—create opportunity.

The Challenge:
As digital agents become part of your workforce, how do you structure, monitor, and measure their impact?
The Reality:
Agent management is the new org design—defining roles, rules, and relationships between human and digital collaborators.
What You’ll Learn:
--- How to design your “agent org chart” and governance structure
--- Metrics and KPIs for managing agent performance and compliance
--- Case studies of early adopters blending human and digital collaboration
Key Takeaway:
Your next workforce plan isn’t headcount—it’s agent count.

The Challenge:
In the rush to automate, it’s easy to forget the human still drives meaning, judgment, and trust.
The Reality:
The future belongs to teams who balance AI scale with human insight—and know when to lean on each.
What You’ll Learn:
--- How to design decision workflows that preserve human accountability
--- Practical examples of “human in the loop” governance in action
--- How to keep culture and ethics at the center of automation initiatives
Key Takeaway:
The loop isn’t closed until the human completes it.

Where are you experimenting on the edge — and what’s holding you back?

The Challenge:
Everyone is chasing the “AI dividend,” but very few teams know how to capture it , or scale it. The gap isn’t the technology. It’s the operating model. Leaders are struggling to translate individual productivity wins into team-level outcomes and enterprise-level value that a CEO or CFO can feel.
The Reality:
AI produces value in three layers , individual, team, enterprise. Most organizations stall at the first. Dorothy has been building the next two: redesigning workflows, structuring human-plus-agent models, and reframing the value story so that a productivity gain becomes something measurable at scale. Her experience shows what it takes to operationalize the dividend, not just talk about it.
What You’ll Learn:
--- How to design your “agent workforce” so value compounds
--- How How to measure productivity gains in a way that resonates with senior leadership
--- How to translate the AI dividend into enterprise-level wins
Key Takeaway:
The AI dividend isn’t a windfall , it’s a discipline. Leaders who connect agent-driven productivity to real business outcomes will define the next era of legal performance.

The Challenge:
Productivity tools can make us faster—but not necessarily better.
The Reality:
True transformation starts when teams move from “doing more” to “doing differently.”
What You’ll Learn:
--- How to identify when productivity peaks and innovation should begin
--- Real examples of teams turning efficiency into enterprise value
--- How to shift focus from outputs to outcomes that matter
Key Takeaway:
Productivity is the warm-up. Progress is the game.

The Challenge:
Innovation budgets are tight—but opportunities for experimentation have never been greater.
The Reality:
The smartest teams are turning pilots, partnerships, and prototypes into “free R&D” engines.
For firms and in-house teams alike, this is the new talent equation:
Curiosity + Adaptability + Digital Resourcefulness = Competitive Advantage.
The question isn’t if you’ll embrace it — it’s how fast you’ll learn to.
What You’ll Learn:
--- Three real-world examples of innovation built through collaboration, not budget
--- How to structure co-innovation projects that deliver mutual value
--- How to leverage partners, vendors, and cross-functional teams as your R&D lab
Key Takeaway:
You don’t need more funding—you need more curiosity.

The Challenge:
Everyone wants AI — but most legal teams are standing on shaky foundations: scattered sources, inconsistent standards, weak governance, and data that isn’t ready for intelligence, automation, or agents. AI fails not because the models aren’t good, but because the data isn’t.
The Reality:
Chad has spent the past year leading a data-first transformation — mapping sources, modernizing governance, building shared definitions, and aligning legal, IT, and security around one question: “Is our data trustworthy enough for AI?” His work shows that the pathway to successful AI adoption is 80% data plumbing, 20% model tuning — and most organizations underestimate that drastically.
What You’ll Learn:
--- The 4 layers of data readiness every legal team must build before scaling AI
--- How to unify legal, IT, security, and business partners around shared data models and governance
--- Case examples from Chad’s journey — what worked, what stalled, and how he accelerated trust and adoption
Key Takeaway:
AI doesn’t transform legal teams: clean, connected, governed data does. Your readiness for tomorrow’s tools starts with the foundation you build today.

The Challenge:
Everyone wants results—but few measure what truly drives them.
The Reality:
OKRs aren’t just a management tool—they’re a mindset shift toward clarity, accountability, and alignment.
What You’ll Learn:
--- How OKRs help legal teams connect daily work to enterprise strategy
--- Examples of legal ops and innovation teams using OKRs effectively
--- How to translate OKR lessons into AI and transformation initiatives
Key Takeaway:
What gets measured gets momentum.

The Challenge:
Legal education hasn’t kept pace with how law is practiced—or how technology is changing it.
The Reality:
The next generation of legal professionals must learn data literacy, system thinking, and creative problem-solving.
What You’ll Learn:
--- What skills and programs the next wave of legal professionals need
--- How firms and in-house teams are building “learn while you lead” cultures
--- The role of mentorship, microlearning, and community in future-proofing talent
Key Takeaway:
The future of legal isn’t being taught—it’s being designed.